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Artificial intelligence tools for molecular analysis of sensitization profiles in patients with atopic dermatitis and bronchial asthma

https://doi.org/10.17650/1726-9784-2024-23-3-26-39

Abstract

Background. The variety of characteristics that should be taken into account in the clinical phenotyping of allergic diseases is currently being discussed. One of such characteristics is the individual spectrum of sensitization. An important stage in modern allergology has become the introduction of molecules / components for the detection of mediated reactions to specific class E immunoglobulins.

Aim. To determine the dominant phenotypes of sensitization in patients with severe atopic dermatitis and bronchial asthma based on the results of molecular diagnostics by the ImmunoCAP Immuno Solid-phase Allergen Chip (ISAC) method using machine learning.

Materials and methods. The study included 100 patients who were candidates for genetically engineered biological therapy (n = 63), severe atopic dermatitis (n = 20), or their combination (n = 17) were included. Allergodiagnosis was performed by the ImmunoCAP ISAC method.

Results. Based on the results of the study, 6 phenotypes were identified. In phenotype 1, pollen molecules (Amb a1, Phl p4) and crossed reactive food molecules (Mal d1, Ara h8, Gly m4, Act d8, Pru p3) are the leading, among epidermal molecules only Fel d1 (epidermal allergen) and Asp f6 (fungal allergen) are found. For phenotype 2, the significant allergens were fungal (Asp f6), epidermal (Can f1, Can f5, Can f6, Fel d1), food (Gad c1) and cross reactive food molecules (Mal d1, Pru p1. Ara h8, Cor a1.0401). In phenotype 4, only 3 allergen groups are present:

epidermal (Fel d1, Fel d2, Can f5, Can f6, Can f3), fungal (Asp f6), and cross food allergy (Jug r3, Pru p3). Phenotype 5 and 6 are dominated by epidermal molecules (Can f1 and Fel d1), true food allergies allergens (Gad c1 and Gal d1 and Gad c1, Gal d1, Gal d3, respectively). In phenotype 3, a combination of the previously labeled molecules is noted.

Conclusion. Each of the identified phenotypes reveals a different set of molecules that can be used in real clinical practice to develop reduced panels, making them more accessible.

About the Authors

D. S. Fomina
City Clinical Hospital No. 52, Moscow Healthcare Department; I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia; Astana Medical University
Russian Federation

Daria S. Fomina

3 Pekhotnaya St., Moscow 123182

Bld. 8, 2 Trubetskaya St., Moscow 119048

49a Beybitshilik St., Astana 010000, Kazakhstan



M. S. Lebedkina
City Clinical Hospital No. 52, Moscow Healthcare Department
Russian Federation

Marina Sergeevna Lebedkina

3 Pekhotnaya St., Moscow 123182



E. A. Nikitina
City Clinical Hospital No. 52, Moscow Healthcare Department; I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia
Russian Federation

Ekaterina A. Nikitina

3 Pekhotnaya St., Moscow 123182

Bld. 8, 2 Trubetskaya St., Moscow 119048



A. D. Dushkin
City Clinical Hospital No. 52, Moscow Healthcare Department; Moscow City Oncology Hospital No. 62, Moscow Healthcare Department
Russian Federation

Alexander D. Dushkin

3 Pekhotnaya St., Moscow 123182

27 Istra, Krasnogorsk city district, Moscow region 143515



A. A. Chernov
City Clinical Hospital No. 52, Moscow Healthcare Department
Russian Federation

Anton A. Chernov

3 Pekhotnaya St., Moscow 123182



Yu. D. Yukhnovskaya
I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia
Russian Federation

Yulia D. Yukhnovskaya

Bld. 8, 2 Trubetskaya St., Moscow 119048



I. V. Evsegneeva
I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia
Russian Federation

Irina V. Evsegneeva

Bld. 8, 2 Trubetskaya St., Moscow 119048



A. V. Karaulov
I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia
Russian Federation

Alexander V. Karaulov

Bld. 8, 2 Trubetskaya St., Moscow 119048



M. A. Lysenko
City Clinical Hospital No. 52, Moscow Healthcare Department; N.I. Pirogov Russian National Research Medical University, Ministry of Health of Russia
Russian Federation

Mariana A. Lysenko

3 Pekhotnaya St., Moscow 123182

1A Ostrovityanova St., Moscow 117513



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Review

For citations:


Fomina D.S., Lebedkina M.S., Nikitina E.A., Dushkin A.D., Chernov A.A., Yukhnovskaya Yu.D., Evsegneeva I.V., Karaulov A.V., Lysenko M.A. Artificial intelligence tools for molecular analysis of sensitization profiles in patients with atopic dermatitis and bronchial asthma. Russian Journal of Biotherapy. 2024;23(3):26-39. (In Russ.) https://doi.org/10.17650/1726-9784-2024-23-3-26-39

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